Semantic segmentation is one of the fundamental Computer Vision tasks which aims to label each pixel in an image with a corresponding class. With the advent of deep networks and the availability of large-scale datasets with ground-truth segmentation annotations, substantial progress has been made in this task [1]}, [2]}, [3]}, [4]}, [5]}. However, as such advances can be attributed to abundant pixel-wise segmentation maps made by manual annotation, which is often labor-intensive, few-shot segmentation task [6]}, [7]} has been introduced to address this, where only a handful of support samples are provided to make a mask prediction for a query, which mitigates the reliance on the labeled data.
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